{"id":"W4380875757","doi":"10.1109/tnnls.2023.3282234","title":"Neural-Network-Based Adaptive Fault-Tolerant Cooperative Control of Heterogeneous Multiagent Systems With Multiple Faults and DoS Attacks","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks and Learning Systems","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Qinglan Project of Jiangsu Province of China; China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Backstepping; Control theory (sociology); Denial-of-service attack; Fault tolerance; Computer science; Actuator; Lyapunov stability; Artificial neural network; Lyapunov function; Nonlinear system; Adaptive control; Control engineering; Engineering; Control (management); Distributed computing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005364819,0.000633901,0.0006122356,0.0002739608,0.0003991444,0.0006884962,0.0009079878,0.0006658562,0.0005335265],"category_scores_gemma":[0.001010344,0.0002143297,0.0003650511,0.0003026189,0.0006047134,0.000680567,0.0007699974,0.0006307287,0.00007963336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006537028,"about_ca_system_score_gemma":0.0005680426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008694958,"about_ca_topic_score_gemma":0.005395319,"domain_scores_codex":[0.9996194,0.00005714222,0.00002542688,0.0001279212,0.0001046777,0.00006559426],"domain_scores_gemma":[0.9995934,0.000114954,0.0001229079,0.00002680693,0.0001201616,0.00002189487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007650378,0.00004052389,0.0006255277,0.0000598637,0.00005152745,0.000152975,0.0001105297,0.9633026,0.00469451,0.004169614,0.0002948641,0.02642096],"study_design_scores_gemma":[0.000004749439,0.00003236689,0.0001045029,0.00000195675,0.000007221106,0.000009056406,0.000006762106,0.9988644,0.0003517508,0.0004979516,0.0001167557,0.000002413804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08999383,0.000520378,0.9046214,0.0002279048,0.0001221322,0.00004474285,0.00002172408,0.0002585699,0.004189234],"genre_scores_gemma":[0.992392,0.0001009943,0.006387992,0.00003418212,0.00001958449,0.00003553273,0.00001503372,0.000004630275,0.001010118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008694958,"threshold_uncertainty_score":0.01728868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584161497690889,"score_gpt":0.2230232192047247,"score_spread":0.2071816042278158,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}